Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling.
Ontology highlight
ABSTRACT: Interest in improved understanding of relationships among soil properties and arsenic (As) bioaccessibility has motivated the use of regression models for As bioaccessibility prediction. However, limits in the numbers and types of soils included in previous studies restrict the usefulness of these models beyond the range of soil conditions evaluated, as evidenced by reduced predictive performance when applied to new data. In response, hierarchical models that consider variability in relationships among soil properties and As bioaccessibility across geographic locations and contaminant sources were developed to predict As bioaccessibility in 139 soils on both a mass fraction (mg/kg) and % basis. The hierarchical approach improved the estimation of As bioaccessibility in studied soils. In ad
SUBMITTER: Nelson CM
PROVIDER: S-EPMC9153852 | biostudies-literature | 2018
REPOSITORIES: biostudies-literature
ACCESS DATA